gpa-prediction 开源项目推荐（10 个）

Hunterdii /AI-Nexus

AI Nexus 🌟 是一套精简的 AI 应用套件，使用 Streamlit 构建。它配备了👗用于时尚分类的StyleScan、🩺用于糖尿病预测的GlycoTrack、🔢用于数字识别的DigitSense、🌸用于虹膜物种识别的IrisWise、🎯用于物体识别的ObjexVision以及🎓带有详细洞察的GPA预测的GradeCast。

Shelton-beep /predicting-gpa-using-lifestyle-factors

Predicting student GPA using lifestyle factors like study habits, sleep, and stress levels. A machine learning model built to help students and educators understand the impact of lifestyle choices on academic performance.

Rohityalavarthy /personalized-academic-guidance-system

AI-powered academic guidance system that predicts student GPA and recommends personalized courses using collaborative filtering, Jaccard similarity, and PageRank algorithms. Built with Python ML backend, Node.js API, and web frontend for real-time academic planning assistance.

devsubhaan /Student-Grade-Predictor

Machine learning pipeline using Ridge, XGBoost and Catboost to predict GPA with ~95-96% R^2

Thejesh06 /insomnia-gpa-prediction

ML pipeline replicating research on student sleep & GPA | Random Forest + SMOTE | Streamlit web app for GPA prediction

Zarharan /Educational-Data-Mining

Data mining on the information of whole Iranian students

MuhammadTamami /student-performance-prediction-system

Machine Learning-based Student GPA Prediction System with Flask API deployment using Linear Regression, Random Forest, and XGBoost.

aman-ali65 /Student-CGPA-Prediction-App

Machine learning web app for estimating student GPA and CGPA from academic, attendance, and extracurricular features through a simple Flask interface.

ankit-chaurasia16 /Student_Lifestyle_Performance_Project

Student lifestyle analysis and academic performance prediction using Python, Pandas, Scikit-learn and Machine Learning. Includes data visualization, outlier detection, model comparison and GPA prediction.

Muhamad-Shahan /Student-Performance-Predictor-GPA

Machine Learning app predicting Student GPA based on study habits, attendance, and parental support. Built with Streamlit and Scikit-Learn to help educators identify at-risk students.